In the display of digital television, tablet or computer, there is a frequent need to change the resolution of image. For example, in a full HD digital TV, the video input source may have a standard definition or a high definition, and in order to display on a full HD television screen, images need to be scaled up. The polyphase interpolation method is a commonly used image scaling method, which has better performance in terms of detail preservation as compared to bilinear interpolation and bicubic interpolation methods, so it is more widely used in the industry.
The interpolation of two-dimensional images can be divided into horizontal interpolation and vertical interpolation, for example, in order to scale up an image of 720×480 into 1920×1080, the image may be first vertically scaled up to 720×1080 and then horizontally scaled up to 1920×1080. The filters used for horizontal interpolation and vertical interpolation may have different taps, and multiple rows of pixels need to be buffered on a chip in order to realize vertical data buffering, so the hardware cost for vertical interpolation is higher than that for horizontal interpolation, and a shorter interpolation filter is usually used in the vertical direction than the horizontal direction in practice. For two-dimensional image interpolation, a conventional circuit with fixed 8-tap (7 order) horizontal filters and 6-tap (5 order) vertical filters is used, whose structural diagram is as shown in FIG. 7-a) wherein the circuit design of a 6-tap filter is as shown in FIG. 7-b), and the circuit design of a 8-tap filter is as shown in FIG. 7-c). It can be seen that filters with different orders have different circuits. In polyphase interpolation, polyphase filters with different orders usually have different performances, and generally speaking, a filter with a higher order means better detail preservation capability, but it also results in the side effects of overshoot and ringing. A polyphase filter with a lower order is not as good as a filter with a higher order in terms of detail preservation capability, but it is better in terms of the side effects of overshoot and ringing. For images having different characteristics, using adaptive filters with different orders can usually achieve better performance than using a fixed single filter. For example, for natural images, using filters with higher orders can achieve better performance, while for graphics, using filters with lower orders can achieve better performance.
In the existing interpolation apparatus, filters suitable for different image types have different orders, while filters with different orders corresponding to different structures, so, in order to select different filters adaptively according to the image characteristics, various interpolation circuits need to be included simultaneously in the conventional circuit design, which cause certain waste of hardware resource. When the chip is taped out, the chip designed only supports a limited number of fixed interpolation filter orders, and the order of the filters cannot be changed, so if the algorithm is changed, the associated hardware has to be re-designed and taped out.